Enhanced target detection using stereoscopic imaging radar

An earlier correspondence reported experiments which suggested that the visibility of a target in clutter could be improved through stereoscopic viewing of high resolution radar images. Here we provide a more thorough discussion on the application of stereo for improving radar detection and recognition. Experiments are reported which confirm and extend the earlier reported results. An example of the use of stereo in a practical system is provided which demonstrates the potential for acquisition of high quality radar stereograms     

Automated Tracking for Aircraft Surveillance Radar Systems

An improved moving target detector (MTD) (a digital signal processor) has been designed, constructed, and tested which successfully rejects all forms of radar clutter while providing reliable detection of all aircraft within the coverage of the radar. The MTD is being tested on both terminal and enroute surveillance radars for the FAA. This processor has been integrated with automatic tracking algorithms to give complete rejection of ground clutter, heavy precipitation, and angels (birds).     

Analysis of queuing behavior of automatic ESM systems

Radar electronic support measures (ESM) systems detect active emitters in a given area and determine their identities and bearings. The high arrival rate of radar pulses in dense emitter environments demands fast automatic processing of arriving pulses so that the ESM system can fulfill its functions properly in real time. Yet, the performance analysis of automatic ESM system in real life Is difficult since both pulse arrivals and widths can be specified only probabilistically. The success of queuing theory in many applications such as computer communication networks and flow-control has encouraged designers to utilize queuing theory in qualifying and judging the performance of automatic ESM systems in dense emitter environments. The queuing behavior of these systems is analytically evaluated under different service disciplines and elaborate computer simulations validate the results. The analysis involves statistical modeling of arrival and departure processes as well as distribution of service times. It permits estimating the blocking probability due to high arrival rates of intercepted radar pulses or due to limited speed of the deinterleaver processor. Queuing analysis is shown to be quite useful to quantitatively assess tradeoffs in ESM systems design     

Automatic recognition of ISAR ship images

Inverse synthetic aperture radar (ISAR) produces images of ships at sea which human operators can be trained to recognize. Because ISAR uses the ship's own varying angular motions (roll, pitch, and yaw) for cross-range resolution, the viewing aspect and cross-range scale factor are continually changing on time scales of a few seconds. This and other characteristics of ISAR imaging make the problem of automatic recognition of ISAR images quite distinct from the recognition of optical images. The nature of ISAR imaging of ships, and single-frame and multiple-frame techniques for segmentation, feature extraction, and classification are described. Results are shown which illustrate a capability for automatic recognition of ISAR ship imagery     

Search radar detection and track with the Hough transform. I.system concept

A method of viewing search radar signals and data is described and analyzed in which the image processing technique of the Hough transform is used to extract detections and simultaneous tracks from multi-dimensional data maps. System design concepts are considered and simulation examples are given that illustrate the concept. The technique offers many advantages when compared with more traditional techniques. These advantages include improved detection, a solution to the range walk problem, flexibility of implementation, elimination of slow scan-rate latency and automatic track acquisition without revisit. The concept is similar to track-before-detect algorithms that use preliminary information from previous scans to aid in target declarations     

Multipath Angle Error Reduction Using Multiple-Target Methods

The usual methods of reducing multipath angle errors in monopulse tracking radar achieve only limited success because they do not attack the root of the problem. A more correct approach is to accept the multipath signal as a second target and utilize a two-target signal processor which angle tracks both wavefronts. The processor will decouple the return signals so that relatively interference-free data on both waves are obtained. In this paper a signal processor for separating signal from (N - 1) multipath components is developed. The processor is then specialized to the case of only one multipath signal and evaluated by a computer simulation. Data show that large improvements are possible as compared to the usual monopulse tracking system. In particular, the usual large bias errors at low elevation angles are eliminated. Tracking precision compares favorably with the theoretically best possible for two-target tracking systems.     

Self-calibrating SSR monopulse receiver

An extension of the monopulse technique for estimating the target azimuth in a secondary surveillance radar (SSR) is considered. The idea is to associate in pairs monopulse measurements coming from the amplitude processor (AP) at the dwell time processing level. This allows the automatic compensation of the bias errors due to the misalignments in the receiver channels, thus eliminating the necessity for periodic system calibration. This dual-pulse technique also allows for the practical use of the dot product receiver as a modification of the AP receiver. This, in turn, implies that the variance of each dual-pulse estimate is uniformly maintained at the monopulse maximum-likelihood level over the whole off-boresight angle (OBA) range     

CWLFM Radar for Ship Detection and Identification

Continuous wave lineal frequency modulated (CWLFM) radar presents some interesting advantages for coast surveillance and control as well as low probability of interception (LPI). This paper presents real results obtained with a radar prototype and processed with ISAR techniques. Also, results of an automatic ship identification system applied to simulated ISAR images are exposed. Moreover, radar behavior with unfavorable meteorological conditions is discussed     

Performance Compparison of Optimum and Conventional MTI and Doppler Processors

The performance of an optimum radar signal processor and more conventional techniques (such as MTI, adaptive MTI, and cqherent integration) are compared. A mathematical method is suggested and applied to several cases of practical interest. A number of operative conditions are discovered in which the conventional processing techniques give very poor performance and the optimum radar processor becomes necessary.     

Doppler Processor Rejection of Range Ambiguous Clutter

Doppler processors are used in radar to separate target returns from clutter. When the clutter is at a range farther than the unambiguous range of the radar, the ability to reject the clutter is degraded. In this article the degradation is analyzed for an N-pulse batch processor with Dolph weighting, and the results show how degradation varies with design sidelobe level.     

Flight test evaluation of a 35 GHz forward looking altimeter forterrain avoidance

Honeywell has conducted a series of flight tests of a 35 GHz digital microprocessor controlled forward looking radar altimeter. A Bell 206L Jet Ranger helicopter was used to evaluate the capability of the sensor as a detector of various types of terrain collision hazards. The sensor was composed of a covert, spread spectrum radar altimeter processor driving a 35 GHz converter and antenna assembly mounted on a steerable platform. Excellent correlation between predicted performance and observed performance was obtained     

Comments on: "Design of MTI Radar on the Basis of Detection Probability"

The main comment of the above paper [1] is that radar integration after MTI processing is not taken into account. For this reason, its numerical results (and curves) show processing losses much higher than practical values. The latter can be obtained in a relatively easy way by means of a computer simulation of the entire signal processor.     

Coherent detection of radar targets in a non-gaussian background

The problem of detecting radar targets against a background of coherent, correlated, non-Gaussian clutter is studied with a two-step procedure. In the first step, the structure of the amplitude and the multivariate probability density functions (pdfs) describing the statistical properties of the clutter is derived. The starting point for this derivation is the basic scattering problem, and the statistics are obtained from an extension of the central limit theorem (CLT). This extension leads to modeling the clutter amplitude statistics by a mixture of Rayleigh distributions. The end product of the first step is a multidimensional pdf in the form of a Gaussian mixture, which is then used in step 2. The aim of step 2 is to derive both the optimal and a suboptimal detection structure for detecting radar targets in this type of clutter. Some performance results for the new detection processor are also given     

Reiterative median cascaded canceler for robust adaptive array processing

A new robust adaptive processor based on reiterative application of the median cascaded canceler (MCC) is presented and called the reiterative median cascaded canceler (RMCC). It is shown that the RMCC processor is a robust replacement for the sample matrix inversion (SMI) adaptive processor and for its equivalent implementations. The MCC, though a robust adaptive processor, has a convergence rate that is dependent on the rank of the input interference-plus-noise covariance matrix for a given number of adaptive degrees of freedom (DOF), N. In contrast, the RMCC, using identical training data as the MCC, exhibits the highly desirable combination of: 1) convergence-robustness to outliers/targets in adaptive weight training data, like the MCC, and 2) fast convergence performance that is independent of the input interference-plus-noise covariance matrix, unlike the MCC. For a number of representative examples, the RMCC is shown to converge using ~ 2.8N samples for any interference rank value as compared with ~ 2N samples for the SMI algorithm. However, the SMI algorithm requires considerably more samples to converge in the presence of outliers/targets, whereas the RMCC does not. Both simulated data as well as measured airborne radar data from the multichannel airborne radar measurements (MCARM) space-time adaptive processing (STAP) database are used to illustrate performance improvements over SMI methods.     

Bayesian gamma mixture model approach to radar target recognition

This paper develops a Bayesian gamma mixture model approach to automatic target recognition (ATR). The specific problem considered is the classification of radar range profiles (RRPs) of military ships. However, the approach developed is relevant to the generic discrimination problem. We model the radar returns (data measurements) from each target as a gamma mixture distribution. Several different motivations for the use of mixture models are put forward, with gamma components being chosen through a physical consideration of radar returns. Bayesian formalism is adopted and we obtain posterior distributions for the parameters of our mixture models. The distributions obtained are too complicated for direct analytical use in a classifier, so Markov chain Monte Carlo (MCMC) techniques are used to provide samples from the distributions. The classification results on the ship data compare favorably with those obtained from two previously published techniques, namely a self-organizing map and a maximum likelihood gamma mixture model classifier.     

Radar Altimeter Optimization for Geodesy Over the Sea

The optimum processor and its accuracy limit for radar altimetry for geodetic use over the sea are studied with a model accounting for random surface reflectivity, sea height variation, additive noise, and pointing errors, and allowing for arbitrary antenna patterns, signal modulations, and other system parameters. The ?threshold? case solution (which can have any specified accuracy) dictates a signal modulation bandwidth just shy of resolving the sea height variation and/or illuminated sea area (as scaled into time delay and ?smeared? by pointing errors). For such a modulation a relatively complete solution is obtained. These results are used to determine practical radar altimeter designs, additionally accounting for antenna size, stability, and peak power restraints. Conditions allowing neglecting of limiting or complicating effects due to temporally varying reflectivity, sea height, and vehicle position are given and shown to be satisfied for a typical satellite.     

Further results on radar pointing error reduction using discreteextended Kalman filtering

A recently proposed method of reducing target glint errors in radar systems using extended Kalman filtering is further extended with the inclusion of and compensation for clutter effects. A discrete target model and discrete Kalman filter (DKF) are used. Simulation results demonstrating the DKF are presented, and the limits on the effectiveness of the method are investigated. The major advantage of the DKF is that it can be implemented in software in the digital processor of the radar, offering flexibility over continuous time filters. The ability of the filter to reduce clutter effects further demonstrates the usefulness of this technique for radar pointing error reduction     

Equal allocation scheduling for data intensive applications

A new analytical model for equal allocation of divisible computation and communication load is developed. Equal allocation of load is attractive in multiple processor systems when real time information on processor and link capacity that is necessary for optimal scheduling is not available. The model includes a detailed accounting of solution reporting time. Equal allocation scheduling is compared with sequential scheduling and a new type of multi-installment scheduling. Aerospace applications include the processing of satellite imagery, radar, and sensor networks.     

A Distribution-Free Doppler Processor

A distribution-free Doppler processor (DFDP) is described. This procedure is applicable to the detection of signals with unknown phase or signals which undergo a change in phase from one observation to the next. The procedure has the characteristic that the false-alarm probability is a constant, independent of the probability distribution of the received data when no signal is present. Also, an estimate of the Doppler frequency, when applied to a Doppler radar processor, is provided.